The objective of the present study was the evaluation of Fourier transform infrared (FTIR) spectroscopy and multispectral imaging (MSI), in tandem with multivariate data analysis, as means of estimating the microbiological quality of sea bream. Farmed whole ungutted fish were stored aerobically at 0, 4 and 8 °C. At regular time intervals, fish samples (i.e. cut portions) were analysed microbiologically, while FTIR and MSI measurements also were acquired at both the skin and flesh sides of the samples. Partial least squares regression (PLSR) models were calibrated to provide quantitative estimations of the microbiological status of fish based on spectral data, in a temperature-independent manner. The PLSR model based on the FTIR data of fish skin exhibited good performance when externally validated, with the coefficient of determination (R 2 ) and the root mean square error (RMSE) being 0.727 and 0.717, respectively. Hence, FTIR spectroscopy appears to be promising for the rapid and non-invasive monitoring of the microbiological spoilage of whole sea bream. On the other hand, the performance of the MSI models was not satisfactory. Nonetheless, as suggested by model optimization results, MSI may also provide useful information with regard to fish microbiological quality, with its definite competence warranting further investigation.